R Notebook

library(tidyverse)
library (car)
library (ridge)

TT <- read_csv("../../data/periods.csv")

Parsed with column specification:
cols(
  V1 = col_double(),
  V2 = col_double(),
  V3 = col_double(),
  V4 = col_double(),
  V5 = col_double(),
  V6 = col_double()
)

badsat <- read_csv("BADSAT.txt")

Parsed with column specification:
cols(
  sat_id = col_double()
)

badsat

for (i in unique(badsat$sat_id)){
  print(i)
 ddi <- filter(dd, sat_id==i)
 testi <- filter(dd, sat_id==i)
 testi <- rbind(select(testi, id, sat_id, epoch, x_sim, y_sim, z_sim, Vx_sim, Vy_sim, Vz_sim), filter(test, sat_id==i))
 
  t1 <- unlist(TT[i+1,1])
  t2 <- unlist(TT[i+1,2])
  t3 <- unlist(TT[i+1,3])
  t4 <- unlist(TT[i+1,4])
  t5 <- unlist(TT[i+1,5])
  t6 <- unlist(TT[i+1,6])
  
  
 lmX <- lm(x ~ epoch+sin(2*pi/t1*epoch)+cos(2*pi/t1*epoch)+sin(4*pi/t1*epoch)+cos(4*pi/t1*epoch)+sin(6*pi/t1*epoch)+cos(6*pi/t1*epoch)+sin(8*pi/t1*epoch)+cos(8*pi/t1*epoch)+sin(10*pi/t1*epoch)+cos(10*pi/t1*epoch)+epoch*sin(2*pi/t1*epoch)+epoch*cos(2*pi/t1*epoch)+epoch*sin(4*pi/t1*epoch)+epoch*cos(4*pi/t1*epoch)+epoch*sin(6*pi/t1*epoch)+epoch*cos(6*pi/t1*epoch)+epoch*sin(8*pi/t1*epoch)+epoch*cos(8*pi/t1*epoch)+epoch*sin(10*pi/t1*epoch)+epoch*cos(10*pi/t1*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmY <- lm(y ~ epoch+sin(2*pi/t2*epoch)+cos(2*pi/t2*epoch)+sin(4*pi/t2*epoch)+cos(4*pi/t2*epoch)+sin(6*pi/t2*epoch)+cos(6*pi/t2*epoch)+sin(8*pi/t2*epoch)+cos(8*pi/t2*epoch)+sin(10*pi/t2*epoch)+cos(10*pi/t2*epoch)+epoch*sin(2*pi/t2*epoch)+epoch*cos(2*pi/t2*epoch)+epoch*sin(4*pi/t2*epoch)+epoch*cos(4*pi/t2*epoch)+epoch*sin(6*pi/t2*epoch)+epoch*cos(6*pi/t2*epoch)+epoch*sin(8*pi/t2*epoch)+epoch*cos(8*pi/t2*epoch)+epoch*sin(10*pi/t2*epoch)+epoch*cos(10*pi/t2*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmZ <- lm(z ~ epoch+sin(2*pi/t3*epoch)+cos(2*pi/t3*epoch)+sin(4*pi/t3*epoch)+cos(4*pi/t3*epoch)+sin(6*pi/t3*epoch)+cos(6*pi/t3*epoch)+sin(8*pi/t3*epoch)+cos(8*pi/t3*epoch)+sin(10*pi/t3*epoch)+cos(10*pi/t3*epoch)+epoch*sin(2*pi/t3*epoch)+epoch*cos(2*pi/t3*epoch)+epoch*sin(4*pi/t3*epoch)+epoch*cos(4*pi/t3*epoch)+epoch*sin(6*pi/t3*epoch)+epoch*cos(6*pi/t3*epoch)+epoch*sin(8*pi/t3*epoch)+epoch*cos(8*pi/t3*epoch)+epoch*sin(10*pi/t3*epoch)+epoch*cos(10*pi/t3*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 lmVx <- lm(Vx ~ epoch+sin(2*pi/t4*epoch)+cos(2*pi/t4*epoch)+sin(4*pi/t4*epoch)+cos(4*pi/t4*epoch)+sin(6*pi/t4*epoch)+cos(6*pi/t4*epoch)+sin(8*pi/t4*epoch)+cos(8*pi/t4*epoch)+sin(10*pi/t4*epoch)+cos(10*pi/t4*epoch)+epoch*sin(2*pi/t4*epoch)+epoch*cos(2*pi/t4*epoch)+epoch*sin(4*pi/t4*epoch)+epoch*cos(4*pi/t4*epoch)+epoch*sin(6*pi/t4*epoch)+epoch*cos(6*pi/t4*epoch)+epoch*sin(8*pi/t4*epoch)+epoch*cos(8*pi/t4*epoch)+epoch*sin(10*pi/t4*epoch)+epoch*cos(10*pi/t4*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVy <- lm(Vy ~ epoch+sin(2*pi/t5*epoch)+cos(2*pi/t5*epoch)+sin(4*pi/t5*epoch)+cos(4*pi/t5*epoch)+sin(6*pi/t5*epoch)+cos(6*pi/t5*epoch)+sin(8*pi/t5*epoch)+cos(8*pi/t5*epoch)+sin(10*pi/t5*epoch)+cos(10*pi/t5*epoch)+epoch*sin(2*pi/t5*epoch)+epoch*cos(2*pi/t5*epoch)+epoch*sin(4*pi/t5*epoch)+epoch*cos(4*pi/t5*epoch)+epoch*sin(6*pi/t5*epoch)+epoch*cos(6*pi/t5*epoch)+epoch*sin(8*pi/t5*epoch)+epoch*cos(8*pi/t5*epoch)+epoch*sin(10*pi/t5*epoch)+epoch*cos(10*pi/t5*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVz <- lm(Vz ~ epoch+sin(2*pi/t6*epoch)+cos(2*pi/t6*epoch)+sin(4*pi/t6*epoch)+cos(4*pi/t6*epoch)+sin(6*pi/t6*epoch)+cos(6*pi/t6*epoch)+sin(8*pi/t6*epoch)+cos(8*pi/t6*epoch)+sin(10*pi/t6*epoch)+cos(10*pi/t6*epoch)+epoch*sin(2*pi/t6*epoch)+epoch*cos(2*pi/t6*epoch)+epoch*sin(4*pi/t6*epoch)+epoch*cos(4*pi/t6*epoch)+epoch*sin(6*pi/t6*epoch)+epoch*cos(6*pi/t6*epoch)+epoch*sin(8*pi/t6*epoch)+epoch*cos(8*pi/t6*epoch)+epoch*sin(10*pi/t6*epoch)+epoch*cos(10*pi/t6*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
  
 if (i == unique(badsat$sat_id)[1]) {
  ans <- data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi))
 } else{
  ans <- rbind(ans, data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi)))
 }
}

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for (i in unique(badsat$sat_id)) {
  print(i)
  sat <- filter(train, sat_id==i)
  sat_pred <- filter(ans, sat_id==i)
  
  plot(sat_pred$epoch, sat_pred$x, col="red", type="l")
  lines(sat$epoch, sat$x, type = "l", col="blue")
}

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for (i in unique(badsat$sat_id)){
  print(i)
 ddi <- filter(dd, sat_id==i)
 testi <- filter(dd, sat_id==i)
 testi <- rbind(select(testi, id, sat_id, epoch, x_sim, y_sim, z_sim, Vx_sim, Vy_sim, Vz_sim), filter(test, sat_id==i))
 
  t1 <- unlist(TT[i+1,1])
  t2 <- unlist(TT[i+1,2])
  t3 <- unlist(TT[i+1,3])
  t4 <- unlist(TT[i+1,4])
  t5 <- unlist(TT[i+1,5])
  t6 <- unlist(TT[i+1,6])
  
  
 lmX <- linearRidge(x ~ epoch+sin(2*pi/t1*epoch)+cos(2*pi/t1*epoch)+sin(4*pi/t1*epoch)+cos(4*pi/t1*epoch)+sin(6*pi/t1*epoch)+cos(6*pi/t1*epoch)+sin(8*pi/t1*epoch)+cos(8*pi/t1*epoch)+sin(10*pi/t1*epoch)+cos(10*pi/t1*epoch)+epoch*sin(2*pi/t1*epoch)+epoch*cos(2*pi/t1*epoch)+epoch*sin(4*pi/t1*epoch)+epoch*cos(4*pi/t1*epoch)+epoch*sin(6*pi/t1*epoch)+epoch*cos(6*pi/t1*epoch)+epoch*sin(8*pi/t1*epoch)+epoch*cos(8*pi/t1*epoch)+epoch*sin(10*pi/t1*epoch)+epoch*cos(10*pi/t1*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi, scaling="scale", lambda = 10^seq(-3,2,.1))
 
 lmY <- linearRidge(y ~ epoch+sin(2*pi/t2*epoch)+cos(2*pi/t2*epoch)+sin(4*pi/t2*epoch)+cos(4*pi/t2*epoch)+sin(6*pi/t2*epoch)+cos(6*pi/t2*epoch)+sin(8*pi/t2*epoch)+cos(8*pi/t2*epoch)+sin(10*pi/t2*epoch)+cos(10*pi/t2*epoch)+epoch*sin(2*pi/t2*epoch)+epoch*cos(2*pi/t2*epoch)+epoch*sin(4*pi/t2*epoch)+epoch*cos(4*pi/t2*epoch)+epoch*sin(6*pi/t2*epoch)+epoch*cos(6*pi/t2*epoch)+epoch*sin(8*pi/t2*epoch)+epoch*cos(8*pi/t2*epoch)+epoch*sin(10*pi/t2*epoch)+epoch*cos(10*pi/t2*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmZ <- linearRidge(z ~ epoch+sin(2*pi/t3*epoch)+cos(2*pi/t3*epoch)+sin(4*pi/t3*epoch)+cos(4*pi/t3*epoch)+sin(6*pi/t3*epoch)+cos(6*pi/t3*epoch)+sin(8*pi/t3*epoch)+cos(8*pi/t3*epoch)+sin(10*pi/t3*epoch)+cos(10*pi/t3*epoch)+epoch*sin(2*pi/t3*epoch)+epoch*cos(2*pi/t3*epoch)+epoch*sin(4*pi/t3*epoch)+epoch*cos(4*pi/t3*epoch)+epoch*sin(6*pi/t3*epoch)+epoch*cos(6*pi/t3*epoch)+epoch*sin(8*pi/t3*epoch)+epoch*cos(8*pi/t3*epoch)+epoch*sin(10*pi/t3*epoch)+epoch*cos(10*pi/t3*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 lmVx <- linearRidge(Vx ~ epoch+sin(2*pi/t4*epoch)+cos(2*pi/t4*epoch)+sin(4*pi/t4*epoch)+cos(4*pi/t4*epoch)+sin(6*pi/t4*epoch)+cos(6*pi/t4*epoch)+sin(8*pi/t4*epoch)+cos(8*pi/t4*epoch)+sin(10*pi/t4*epoch)+cos(10*pi/t4*epoch)+epoch*sin(2*pi/t4*epoch)+epoch*cos(2*pi/t4*epoch)+epoch*sin(4*pi/t4*epoch)+epoch*cos(4*pi/t4*epoch)+epoch*sin(6*pi/t4*epoch)+epoch*cos(6*pi/t4*epoch)+epoch*sin(8*pi/t4*epoch)+epoch*cos(8*pi/t4*epoch)+epoch*sin(10*pi/t4*epoch)+epoch*cos(10*pi/t4*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVy <- linearRidge(Vy ~ epoch+sin(2*pi/t5*epoch)+cos(2*pi/t5*epoch)+sin(4*pi/t5*epoch)+cos(4*pi/t5*epoch)+sin(6*pi/t5*epoch)+cos(6*pi/t5*epoch)+sin(8*pi/t5*epoch)+cos(8*pi/t5*epoch)+sin(10*pi/t5*epoch)+cos(10*pi/t5*epoch)+epoch*sin(2*pi/t5*epoch)+epoch*cos(2*pi/t5*epoch)+epoch*sin(4*pi/t5*epoch)+epoch*cos(4*pi/t5*epoch)+epoch*sin(6*pi/t5*epoch)+epoch*cos(6*pi/t5*epoch)+epoch*sin(8*pi/t5*epoch)+epoch*cos(8*pi/t5*epoch)+epoch*sin(10*pi/t5*epoch)+epoch*cos(10*pi/t5*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVz <- linearRidge(Vz ~ epoch+sin(2*pi/t6*epoch)+cos(2*pi/t6*epoch)+sin(4*pi/t6*epoch)+cos(4*pi/t6*epoch)+sin(6*pi/t6*epoch)+cos(6*pi/t6*epoch)+sin(8*pi/t6*epoch)+cos(8*pi/t6*epoch)+sin(10*pi/t6*epoch)+cos(10*pi/t6*epoch)+epoch*sin(2*pi/t6*epoch)+epoch*cos(2*pi/t6*epoch)+epoch*sin(4*pi/t6*epoch)+epoch*cos(4*pi/t6*epoch)+epoch*sin(6*pi/t6*epoch)+epoch*cos(6*pi/t6*epoch)+epoch*sin(8*pi/t6*epoch)+epoch*cos(8*pi/t6*epoch)+epoch*sin(10*pi/t6*epoch)+epoch*cos(10*pi/t6*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
  
 if (i == unique(badsat$sat_id)[1]) {
  ans <- data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi))
 } else{
  ans <- rbind(ans, data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi)))
 }
}

[1] 0

Error in as.matrix(mm) %*% beta : argumentos no compatibles

for (i in unique(badsat$sat_id)) {
  print(i)
  sat <- filter(train, sat_id==i)
  sat_pred <- filter(ans, sat_id==i)
  
  plot(sat_pred$epoch, sat_pred$x, col="red", type="l")
  lines(sat$epoch, sat$x, type = "l", col="blue")
}

[1] 0
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minims <- function(v) {
  ans <- c()
  for (i in 2:(length(v)-1)) {
    if (v[i] < v[i+1] && v[i] < v[i-1]) {
      ans <- c(ans, i)
    }
  }
  ans
}
maxims <- function(v) {
  ans <- c()
  for (i in 2:(length(v)-1)) {
    if (v[i] > v[i+1] && v[i] > v[i-1]) {
      ans <- c(ans, i)
    }
  }
  ans
}

ddi <- filter(train, sat_id==badsat$sat_id[3])
tti <- data.frame(id=ddi$id, sat_id=ddi$sat_id, epoch=ddi$epoch, x=predict(lmX, ddi), y=predict(lmY, ddi), z=predict(lmZ, ddi), Vx=predict(lmVX, ddi), Vy=predict(lmVY, ddi), VZ=predict(lmVZ, ddi))
tti <- filter(ans, sat_id==badsat$sat_id[3])
minddiX <- ddi[minims(ddi$x),]
rectaXdown <- lm(x ~ epoch, data = minddiX)
maxddiX <- ddi[maxims(ddi$x),]
rectaXup <- lm(x ~ epoch, data = maxddiX)
minttiX <- tti[minims(tti$x),]
rectaXdownt <- lm(x ~ epoch, data = minttiX)
maxttiX <- tti[maxims(tti$x),]
rectaXupt <- lm(x ~ epoch, data = maxttiX)
plot(minttiX$epoch, minttiX$x)
points(maxttiX$epoch, maxttiX$x)

c <- predict(rectaXdown, tti)
d <- predict(rectaXup, tti)
tti$x <- (tti$x - predict(rectaXdownt, tti)) * (d-c) / (predict(rectaXupt,tti) - predict(rectaXdownt, tti)) + c
plot(tti$epoch, tti$x, col="red", type="p", ylim=c(min(sat$x),max(sat$x)))
lines(sat$epoch, sat$x, type = "p", col="blue")

sat <- filter(train, sat_id==badsat$sat_id[3])
sat_pred <- filter(ans, sat_id==badsat$sat_id[3])
write_csv(ddi, "train.csv", quote=F)
write_csv(tti, "submission.csv", quote=F)

---
title: "R Notebook"
output: html_notebook
---

Libreias
```{r}
library(tidyverse)
library (car)
library (ridge)
```

Data
```{r}
train <- read_csv("../../data/train.csv")
test <- read_csv("../../data/test.csv")

test$epoch <- as.numeric(as.POSIXct(test$epoch))
train$epoch <- as.numeric(as.POSIXct(train$epoch))
test$epoch <- test$epoch - min(train$epoch)
train$epoch <- train$epoch - min(train$epoch)

train$x <- as.numeric(train$x)
train$y <- as.numeric(train$y)
train$z <- as.numeric(train$z)
train$Vx <- as.numeric(train$Vx)
train$Vy <- as.numeric(train$Vy)
train$Vz <- as.numeric(train$Vz)

TT <- read_csv("../../data/periods.csv")
```

Satelites malo
```{r}
badsat <- read_csv("BADSAT.txt")
badsat
```

Normal regression
```{r}
for (i in unique(badsat$sat_id)){
  print(i)
 ddi <- filter(dd, sat_id==i)
 testi <- filter(dd, sat_id==i)
 testi <- rbind(select(testi, id, sat_id, epoch, x_sim, y_sim, z_sim, Vx_sim, Vy_sim, Vz_sim), filter(test, sat_id==i))
 
  t1 <- unlist(TT[i+1,1])
  t2 <- unlist(TT[i+1,2])
  t3 <- unlist(TT[i+1,3])
  t4 <- unlist(TT[i+1,4])
  t5 <- unlist(TT[i+1,5])
  t6 <- unlist(TT[i+1,6])
  
  
 lmX <- lm(x ~ epoch+sin(2*pi/t1*epoch)+cos(2*pi/t1*epoch)+sin(4*pi/t1*epoch)+cos(4*pi/t1*epoch)+sin(6*pi/t1*epoch)+cos(6*pi/t1*epoch)+sin(8*pi/t1*epoch)+cos(8*pi/t1*epoch)+sin(10*pi/t1*epoch)+cos(10*pi/t1*epoch)+epoch*sin(2*pi/t1*epoch)+epoch*cos(2*pi/t1*epoch)+epoch*sin(4*pi/t1*epoch)+epoch*cos(4*pi/t1*epoch)+epoch*sin(6*pi/t1*epoch)+epoch*cos(6*pi/t1*epoch)+epoch*sin(8*pi/t1*epoch)+epoch*cos(8*pi/t1*epoch)+epoch*sin(10*pi/t1*epoch)+epoch*cos(10*pi/t1*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmY <- lm(y ~ epoch+sin(2*pi/t2*epoch)+cos(2*pi/t2*epoch)+sin(4*pi/t2*epoch)+cos(4*pi/t2*epoch)+sin(6*pi/t2*epoch)+cos(6*pi/t2*epoch)+sin(8*pi/t2*epoch)+cos(8*pi/t2*epoch)+sin(10*pi/t2*epoch)+cos(10*pi/t2*epoch)+epoch*sin(2*pi/t2*epoch)+epoch*cos(2*pi/t2*epoch)+epoch*sin(4*pi/t2*epoch)+epoch*cos(4*pi/t2*epoch)+epoch*sin(6*pi/t2*epoch)+epoch*cos(6*pi/t2*epoch)+epoch*sin(8*pi/t2*epoch)+epoch*cos(8*pi/t2*epoch)+epoch*sin(10*pi/t2*epoch)+epoch*cos(10*pi/t2*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmZ <- lm(z ~ epoch+sin(2*pi/t3*epoch)+cos(2*pi/t3*epoch)+sin(4*pi/t3*epoch)+cos(4*pi/t3*epoch)+sin(6*pi/t3*epoch)+cos(6*pi/t3*epoch)+sin(8*pi/t3*epoch)+cos(8*pi/t3*epoch)+sin(10*pi/t3*epoch)+cos(10*pi/t3*epoch)+epoch*sin(2*pi/t3*epoch)+epoch*cos(2*pi/t3*epoch)+epoch*sin(4*pi/t3*epoch)+epoch*cos(4*pi/t3*epoch)+epoch*sin(6*pi/t3*epoch)+epoch*cos(6*pi/t3*epoch)+epoch*sin(8*pi/t3*epoch)+epoch*cos(8*pi/t3*epoch)+epoch*sin(10*pi/t3*epoch)+epoch*cos(10*pi/t3*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)

 lmVx <- lm(Vx ~ epoch+sin(2*pi/t4*epoch)+cos(2*pi/t4*epoch)+sin(4*pi/t4*epoch)+cos(4*pi/t4*epoch)+sin(6*pi/t4*epoch)+cos(6*pi/t4*epoch)+sin(8*pi/t4*epoch)+cos(8*pi/t4*epoch)+sin(10*pi/t4*epoch)+cos(10*pi/t4*epoch)+epoch*sin(2*pi/t4*epoch)+epoch*cos(2*pi/t4*epoch)+epoch*sin(4*pi/t4*epoch)+epoch*cos(4*pi/t4*epoch)+epoch*sin(6*pi/t4*epoch)+epoch*cos(6*pi/t4*epoch)+epoch*sin(8*pi/t4*epoch)+epoch*cos(8*pi/t4*epoch)+epoch*sin(10*pi/t4*epoch)+epoch*cos(10*pi/t4*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVy <- lm(Vy ~ epoch+sin(2*pi/t5*epoch)+cos(2*pi/t5*epoch)+sin(4*pi/t5*epoch)+cos(4*pi/t5*epoch)+sin(6*pi/t5*epoch)+cos(6*pi/t5*epoch)+sin(8*pi/t5*epoch)+cos(8*pi/t5*epoch)+sin(10*pi/t5*epoch)+cos(10*pi/t5*epoch)+epoch*sin(2*pi/t5*epoch)+epoch*cos(2*pi/t5*epoch)+epoch*sin(4*pi/t5*epoch)+epoch*cos(4*pi/t5*epoch)+epoch*sin(6*pi/t5*epoch)+epoch*cos(6*pi/t5*epoch)+epoch*sin(8*pi/t5*epoch)+epoch*cos(8*pi/t5*epoch)+epoch*sin(10*pi/t5*epoch)+epoch*cos(10*pi/t5*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVz <- lm(Vz ~ epoch+sin(2*pi/t6*epoch)+cos(2*pi/t6*epoch)+sin(4*pi/t6*epoch)+cos(4*pi/t6*epoch)+sin(6*pi/t6*epoch)+cos(6*pi/t6*epoch)+sin(8*pi/t6*epoch)+cos(8*pi/t6*epoch)+sin(10*pi/t6*epoch)+cos(10*pi/t6*epoch)+epoch*sin(2*pi/t6*epoch)+epoch*cos(2*pi/t6*epoch)+epoch*sin(4*pi/t6*epoch)+epoch*cos(4*pi/t6*epoch)+epoch*sin(6*pi/t6*epoch)+epoch*cos(6*pi/t6*epoch)+epoch*sin(8*pi/t6*epoch)+epoch*cos(8*pi/t6*epoch)+epoch*sin(10*pi/t6*epoch)+epoch*cos(10*pi/t6*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
  
 if (i == unique(badsat$sat_id)[1]) {
  ans <- data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi))
 } else{
  ans <- rbind(ans, data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi)))
 }
}
```

```{r}
for (i in unique(badsat$sat_id)) {
  print(i)
  sat <- filter(train, sat_id==i)
  sat_pred <- filter(ans, sat_id==i)
  
  plot(sat_pred$epoch, sat_pred$x, col="red", type="l")
  lines(sat$epoch, sat$x, type = "l", col="blue")
}
```

Ridge regression
```{r}
for (i in unique(badsat$sat_id)){
  print(i)
 ddi <- filter(dd, sat_id==i)
 testi <- filter(dd, sat_id==i)
 testi <- rbind(select(testi, id, sat_id, epoch, x_sim, y_sim, z_sim, Vx_sim, Vy_sim, Vz_sim), filter(test, sat_id==i))
 
  t1 <- unlist(TT[i+1,1])
  t2 <- unlist(TT[i+1,2])
  t3 <- unlist(TT[i+1,3])
  t4 <- unlist(TT[i+1,4])
  t5 <- unlist(TT[i+1,5])
  t6 <- unlist(TT[i+1,6])
  
  
 lmX <- linearRidge(x ~ epoch+sin(2*pi/t1*epoch)+cos(2*pi/t1*epoch)+sin(4*pi/t1*epoch)+cos(4*pi/t1*epoch)+sin(6*pi/t1*epoch)+cos(6*pi/t1*epoch)+sin(8*pi/t1*epoch)+cos(8*pi/t1*epoch)+sin(10*pi/t1*epoch)+cos(10*pi/t1*epoch)+epoch*sin(2*pi/t1*epoch)+epoch*cos(2*pi/t1*epoch)+epoch*sin(4*pi/t1*epoch)+epoch*cos(4*pi/t1*epoch)+epoch*sin(6*pi/t1*epoch)+epoch*cos(6*pi/t1*epoch)+epoch*sin(8*pi/t1*epoch)+epoch*cos(8*pi/t1*epoch)+epoch*sin(10*pi/t1*epoch)+epoch*cos(10*pi/t1*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi, scaling="scale", lambda = 10^seq(-3,2,.1))
 
 lmY <- linearRidge(y ~ epoch+sin(2*pi/t2*epoch)+cos(2*pi/t2*epoch)+sin(4*pi/t2*epoch)+cos(4*pi/t2*epoch)+sin(6*pi/t2*epoch)+cos(6*pi/t2*epoch)+sin(8*pi/t2*epoch)+cos(8*pi/t2*epoch)+sin(10*pi/t2*epoch)+cos(10*pi/t2*epoch)+epoch*sin(2*pi/t2*epoch)+epoch*cos(2*pi/t2*epoch)+epoch*sin(4*pi/t2*epoch)+epoch*cos(4*pi/t2*epoch)+epoch*sin(6*pi/t2*epoch)+epoch*cos(6*pi/t2*epoch)+epoch*sin(8*pi/t2*epoch)+epoch*cos(8*pi/t2*epoch)+epoch*sin(10*pi/t2*epoch)+epoch*cos(10*pi/t2*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmZ <- linearRidge(z ~ epoch+sin(2*pi/t3*epoch)+cos(2*pi/t3*epoch)+sin(4*pi/t3*epoch)+cos(4*pi/t3*epoch)+sin(6*pi/t3*epoch)+cos(6*pi/t3*epoch)+sin(8*pi/t3*epoch)+cos(8*pi/t3*epoch)+sin(10*pi/t3*epoch)+cos(10*pi/t3*epoch)+epoch*sin(2*pi/t3*epoch)+epoch*cos(2*pi/t3*epoch)+epoch*sin(4*pi/t3*epoch)+epoch*cos(4*pi/t3*epoch)+epoch*sin(6*pi/t3*epoch)+epoch*cos(6*pi/t3*epoch)+epoch*sin(8*pi/t3*epoch)+epoch*cos(8*pi/t3*epoch)+epoch*sin(10*pi/t3*epoch)+epoch*cos(10*pi/t3*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)

 lmVx <- linearRidge(Vx ~ epoch+sin(2*pi/t4*epoch)+cos(2*pi/t4*epoch)+sin(4*pi/t4*epoch)+cos(4*pi/t4*epoch)+sin(6*pi/t4*epoch)+cos(6*pi/t4*epoch)+sin(8*pi/t4*epoch)+cos(8*pi/t4*epoch)+sin(10*pi/t4*epoch)+cos(10*pi/t4*epoch)+epoch*sin(2*pi/t4*epoch)+epoch*cos(2*pi/t4*epoch)+epoch*sin(4*pi/t4*epoch)+epoch*cos(4*pi/t4*epoch)+epoch*sin(6*pi/t4*epoch)+epoch*cos(6*pi/t4*epoch)+epoch*sin(8*pi/t4*epoch)+epoch*cos(8*pi/t4*epoch)+epoch*sin(10*pi/t4*epoch)+epoch*cos(10*pi/t4*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVy <- linearRidge(Vy ~ epoch+sin(2*pi/t5*epoch)+cos(2*pi/t5*epoch)+sin(4*pi/t5*epoch)+cos(4*pi/t5*epoch)+sin(6*pi/t5*epoch)+cos(6*pi/t5*epoch)+sin(8*pi/t5*epoch)+cos(8*pi/t5*epoch)+sin(10*pi/t5*epoch)+cos(10*pi/t5*epoch)+epoch*sin(2*pi/t5*epoch)+epoch*cos(2*pi/t5*epoch)+epoch*sin(4*pi/t5*epoch)+epoch*cos(4*pi/t5*epoch)+epoch*sin(6*pi/t5*epoch)+epoch*cos(6*pi/t5*epoch)+epoch*sin(8*pi/t5*epoch)+epoch*cos(8*pi/t5*epoch)+epoch*sin(10*pi/t5*epoch)+epoch*cos(10*pi/t5*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
 lmVz <- linearRidge(Vz ~ epoch+sin(2*pi/t6*epoch)+cos(2*pi/t6*epoch)+sin(4*pi/t6*epoch)+cos(4*pi/t6*epoch)+sin(6*pi/t6*epoch)+cos(6*pi/t6*epoch)+sin(8*pi/t6*epoch)+cos(8*pi/t6*epoch)+sin(10*pi/t6*epoch)+cos(10*pi/t6*epoch)+epoch*sin(2*pi/t6*epoch)+epoch*cos(2*pi/t6*epoch)+epoch*sin(4*pi/t6*epoch)+epoch*cos(4*pi/t6*epoch)+epoch*sin(6*pi/t6*epoch)+epoch*cos(6*pi/t6*epoch)+epoch*sin(8*pi/t6*epoch)+epoch*cos(8*pi/t6*epoch)+epoch*sin(10*pi/t6*epoch)+epoch*cos(10*pi/t6*epoch)+x_sim+y_sim+z_sim+Vx_sim+Vy_sim+Vz_sim, ddi)
 
  
 if (i == unique(badsat$sat_id)[1]) {
  ans <- data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi))
 } else{
  ans <- rbind(ans, data.frame(id = testi$id, sat_id=testi$sat_id, epoch=testi$epoch, x=predict(lmX, testi), y=predict(lmY, testi), z=predict(lmZ, testi), Vx=predict(lmVx, testi), Vy=predict(lmVy, testi), Vz=predict(lmVz, testi)))
 }
}
```

```{r}
for (i in unique(badsat$sat_id)) {
  print(i)
  sat <- filter(train, sat_id==i)
  sat_pred <- filter(ans, sat_id==i)
  
  plot(sat_pred$epoch, sat_pred$x, col="red", type="l")
  lines(sat$epoch, sat$x, type = "l", col="blue")
}
```


```{r}
minims <- function(v) {
  ans <- c()
  for (i in 2:(length(v)-1)) {
    if (v[i] < v[i+1] && v[i] < v[i-1]) {
      ans <- c(ans, i)
    }
  }
  ans
}

maxims <- function(v) {
  ans <- c()
  for (i in 2:(length(v)-1)) {
    if (v[i] > v[i+1] && v[i] > v[i-1]) {
      ans <- c(ans, i)
    }
  }
  ans
}
```

```{r}
ddi <- filter(train, sat_id==badsat$sat_id[3])
tti <- data.frame(id=ddi$id, sat_id=ddi$sat_id, epoch=ddi$epoch, x=predict(lmX, ddi), y=predict(lmY, ddi), z=predict(lmZ, ddi), Vx=predict(lmVX, ddi), Vy=predict(lmVY, ddi), VZ=predict(lmVZ, ddi))
tti <- filter(ans, sat_id==badsat$sat_id[3])

minddiX <- ddi[minims(ddi$x),]
rectaXdown <- lm(x ~ epoch, data = minddiX)
maxddiX <- ddi[maxims(ddi$x),]
rectaXup <- lm(x ~ epoch, data = maxddiX)

minttiX <- tti[minims(tti$x),]
rectaXdownt <- lm(x ~ epoch, data = minttiX)
maxttiX <- tti[maxims(tti$x),]
rectaXupt <- lm(x ~ epoch, data = maxttiX)
plot(minttiX$epoch, minttiX$x)
points(maxttiX$epoch, maxttiX$x)

c <- predict(rectaXdown, tti)
d <- predict(rectaXup, tti)

tti$x <- (tti$x - predict(rectaXdownt, tti)) * (d-c) / (predict(rectaXupt,tti) - predict(rectaXdownt, tti)) + c

plot(tti$epoch, tti$x, col="red", type="p", ylim=c(min(sat$x),max(sat$x)))
lines(sat$epoch, sat$x, type = "p", col="blue")
```
Exportar
```{r}
sat <- filter(train, sat_id==badsat$sat_id[3])
sat_pred <- filter(ans, sat_id==badsat$sat_id[3])

write_csv(ddi, "train.csv", quote=F)
write_csv(tti, "submission.csv", quote=F)
```





